Prenatal Polydrug Exposure: Effects of Timing on Functional Connectivity at Birth

Presented During:

Tuesday, June 25, 2024: 12:00 PM - 1:15 PM
COEX  
Room: Hall D 2  

Poster No:

386 

Submission Type:

Abstract Submission 

Authors:

Janelle Liu1, Rina Eiden2, Karen Grewen3, Wei Gao4

Institutions:

1Cedars-Sinai Medical Center, Los Angeles, CA, 2Pennsylvania State University, University Park, PA, 3University of North Carolina at Chapel Hill, Chapel Hill, NC, 4Cedars Sinai Medical Center, Los Angeles, CA

First Author:

Janelle Liu  
Cedars-Sinai Medical Center
Los Angeles, CA

Co-Author(s):

Rina Eiden  
Pennsylvania State University
University Park, PA
Karen Grewen  
University of North Carolina at Chapel Hill
Chapel Hill, NC
Wei Gao  
Cedars Sinai Medical Center
Los Angeles, CA

Introduction:

Prenatal drug exposure (PDE) impacts infant brain development with documented long-term consequences (Ross 2015). Functional magnetic resonance imaging (fMRI) studies of infants and youth with PDE reveal aberrant brain functional connectivity (Salzwedel 2020). Animal models demonstrate that PDE timing significantly impacts offspring outcome (Byrnes 2018), but most human fMRI studies use a binary categorization to assess drug exposure, limiting the ability to detect timing effects associated with PDE. Here, we use resting-state fMRI (rsfMRI) to characterize timing-related effects of PDE on the neonatal functional connectome. For the first time, we examine neural mechanisms associated with full PDE across all three trimesters (PDE-F) and partial PDE during only the first and/or second trimester (PDE-T1T2).

Methods:

Subjects included drug-free controls (CTR; n=24) and neonates with PDE (n=85). The PDE group was separated into subgroups based on whether infants experienced full exposure to any drugs across all three trimesters (PDE-F; n=49) or partial exposure to any drugs during only the first and/or second trimester (PDE-T1T2; n=21). The Timeline Follow Back (TLFB; Robinson 2014) calendar/interview was conducted to assess prenatal frequency of drug use in each trimester across 9 drug categories (alcohol, nicotine, marijuana, cocaine, opioids, medication for opioid use disorder, stimulants, depressants, other). RsfMRI scans were acquired during natural sleep at 2 weeks of age. Groups were matched on sex, race, gestational age at birth, gestational age at scan, area deprivation index, and motion. Birthweight, maternal education, and maternal depression were included as covariates of no interest in all analyses to control for group differences in these variables. Functional connectivity measures were derived using a neonate functional parcellation-based atlas (Shi 2018). For each seed region of interest (ROI; n=223), the average time series was extracted and correlated with every other ROI in the brain. Next, linear regression was conducted to detect significant functional connectivity differences between the groups. Two summary measures were used: 1) the percentage of connections showing differences at p<.05, and 2) the percentage of connections with at least a medium effect size (bias-corrected Hedge's g>.5; Nakagawa 2007). These were calculated and assigned to the seed ROI. These processes were repeated for all ROIs to generate heatmaps indicating pairwise between-group differences in functional connectivity between each ROI and the whole brain.

Results:

Compared to CTR, PDE infants showed differences in connectivity localized to visual, subcortical, parietal, and temporal areas. Compared with CTR, PDE-F infants showed differences mainly in parietal, subcortical, frontal, and sensorimotor regions, whereas PDE-T1T2 infants showed differences in visual frontal, temporal, and parietal areas. Direct comparison between PDE-F and PDE-T1T2 revealed widespread differences in temporal, subcortical, frontal, sensorimotor, and parietal regions. Consistent results were observed using the Hedge's g effect size as a threshold, larger differences were observed between PDE-T1T2 and CTR than between PDE-F and CTR.
Supporting Image: Figure1.jpg
 

Conclusions:

At birth, the timing of PDE is associated with distinct effects, with PDE during the first and/or second trimester having the largest impact on early brain development. This result is surprising and may be related to the PDE-T1T2 mothers being more homogenous in their drug usage (predominantly alcohol and nicotine). By contrast, the PDE-F mothers had more heterogeneity in their drug usage, which may have resulted in smaller effects due to possible cancellation effects of different drug exposures. However, widespread functional connectivity differences between PDE-F and PDE-T1T2 point toward potential interactions between differential timing of PDE and specific neurodevelopmental processes during the prenatal period.

Disorders of the Nervous System:

Neurodevelopmental/ Early Life (eg. ADHD, autism) 1

Higher Cognitive Functions:

Higher Cognitive Functions Other

Lifespan Development:

Early life, Adolescence, Aging

Modeling and Analysis Methods:

fMRI Connectivity and Network Modeling 2

Keywords:

Cognition
Development
FUNCTIONAL MRI
PEDIATRIC
Other - Connectivity; Infant; Prenatal drug exposure

1|2Indicates the priority used for review

Provide references using author date format

Byrnes, E. (2018), ‘Modeling prenatal opioid exposure in animals: Current findings and future directions’, Front Neuroendocrin, vol. 51, pp. 1-13.
Nakagawa, S. (2007), ‘Effect size, confidence interval and statistical significance: A practical guide for biologists’, Biol Rev, vol. 82, no. 4, pp. 591-605.
Robinson, S. (2014), ‘Reliability of the Timeline Followback for cocaine, cannabis, and cigarette use’, Psych Addic Behav, vol. 28, no. 1, pp. 154-162.
Ross, E. (2015), ‘Developmental consequences of fetal exposure to drugs: What we know and what we still must learn’, Neuropsychopharm, vol. 40, no. 1, pp. 61-87.
Salzwedel, A. (2020), ‘Functional dissection of prenatal drug effects on baby brain and behavioral development’, Hum Brain Mapp, vol. 41, pp. 4789–4715.
Shi, F. (2018), ‘Functional brain parcellations of the infant brain and the associated developmental trends’, Cereb Cortex, vol. 28, no. 4, pp. 1358-1368.